The content of a digital image can have considerable impact on the compression of the digital image, both in terms of compression efficiency and compression artifacts. Pictorial regions in an image are not efficiently compressed using compression algorithms designed for the compression of text. Similarly, text images are not efficiently compressed using compression algorithms that are designed and optimized for pictorial content. Not only is compression efficiency affected when a compression algorithm designed for one type of image content is used on a different type of image content, but the decoded image may exhibit annoying compression artifacts.
Further, image enhancement algorithms designed to sharpen text, if applied to pictorial image content, may produce visually annoying artifacts in some areas of the pictorial content. In particular, those areas of the pictorial content containing strong edges may be affected. While smoothing operations may enhance a natural image, the smoothing of text regions is seldom desirable.
The detection of regions of a particular content type in a digital image can improve compression efficiency, reduce compression artifacts, and improve image quality when used in conjunction with a compression algorithm or image enhancement algorithm designed for the particular type of content.
The semantic labeling of image regions based on content is also useful in document management systems and image databases.
Reliable and efficient detection of regions of pictorial content type and other image regions in digital images is desirable.